Frequently, insufficient measurements are available for properly characterizing the exposure profiles of similarly exposed groups (SEGs) of workers. In such circumstances, occupational hygienists use their professional judgment and other qualitative and semi-quantitative information to supplement the actual exposure measurements in arriving at decisions. There is clearly a need to validate such subjective assessments of exposure and develop a logically coherent framework that integrates these subjective judgments with actual exposure measurements, and thus leverage both sources of information. The overall goal of the proposed research is to develop and validate an efficient, performance-based exposure assessment strategy that combines subjective judgments and actual measurements, and arrives at the correct decision using the least number of measurements. The specific goals of the research are: (1) to assess the accuracy of subjective assessments of exposure by professional hygienists; (2) to identify the determinants of accurate subjective assessments of exposure by occupational hygienists (such as seniority, exposure assessment experience, educational backgrounds), and to determine the sensitivity of their subjective exposure assessments to these determinants; (3) to develop a Bayesian probabilistic framework for efficient decision making regarding exposures that integrates actual monitoring data and subjective estimates of exposures to arrive at correct decisions using the least number of measurements. The methodology will be developed using a large occupational exposure dataset from 3M Company, and probabilistic professional judgments obtained from occupational hygienists employed at 3M Company.